Effects of Temperature upon Water Turnover in Fish Ponds in Northern Thailand
Bibliographic record
Abstract
Fish culture in earthen ponds is an important source of income for farmers in northern Thailand. Water quality in ponds has strong impacts on fish production farmers’ return and is sensitive to weather and climate. Low levels of dissolved oxygen in fish ponds are major cause of mass mortality. Stratification with depth in ponds followed by rapid turnover or exchange of surface and bottom water can expose fish to dangerously low dissolved oxygen levels. The main purpose of this study was to observe the effects of weather on stratification and subsequent water turnover in fish ponds in northern Thailand, especially in the winter and rainy season, when stratification was expected to be most severe. Temperature and water quality measurements were made in fish ponds at 18 farms with depths ranged from 0.8-2.0 m and size of 0.16-0.64 ha. Measurements were made during January and May 2013. Fish farm pond sites were divided into two groups based on elevation above sea level: low (400 masl) and categorized into 3 types of farming: commercial, integrated and subsistence. In lower elevation sites, water turnover occurred at night between 22.00 and 02.00 in winter and between 18.00 and 02.00 in rainy season. At higher elevation, turnover occurred in ponds between 20.00 and 22.00 in winter and between 14.00 and 18.00 in rainy season. Turnover was slower in the lower elevation than in higher elevation zones and generally occurred earlier during the rainy season than in the winter. Mean DO in winter was significantly higher (p<0.05) than in rainy season, whilst water temperature and amount of ammonia-nitrogen during the rainy season was significantly higher (p<0.05) than in winter. Turnover improves distribution of dissolved oxygen through the water column and minimizes organic matter accumulation. Cloud cover during the rainy season may have contributed to limit oxygen production and thus may have significantly affect water quality in ponds. Fish farmers should consider more explicitly the role of temperature and cloud conditions when managing dissolved oxygen levels in their fish ponds. Therefore, efficient pond aeration or pond mixing strategies for reducing stratification still plays an important component for providing sound pond management in tilapia production ponds.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".